Head wearable light therapy device

ABSTRACT

Systems and methods are described for treatment of neurological conditions in which transcranial illumination using infrared, near-infrared and/or red wavelengths of light are delivered into the brain of a patient using a portable head wearable device. Arrays of light emitters are simultaneously controlled to provide a selected power density and distribution during a therapeutic session to treat a condition of the patient. An external controller such as a touchscreen tablet or laptop computer can be used to select illumination parameters for each patient. The system can be used to provide treatment to children such as those having autism spectrum disorder (ASD).

CROSS REFERENCE TO RELATED APPLICATIONS

This application is continuation of U.S. Application No. 17/769,708filed on Apr. 15, 2022 which is a 35 U.S.C. § 371 national stage filingof International Application No. PCT/US2020/055782, filed on Oct. 15,2020, which claims priority to U.S. Provisional Application No.63/033,756, filed Jun. 2, 2020, U.S. Provisional Application No.62/940,788, filed Nov. 26, 2019, and U.S. Provisional Application No.62/915,221, filed Oct. 15, 2019, the entire contents of each of theabove applications being incorporated herein by reference. Thisapplication is also related to U.S. Design Application No. 29/728,109,filed Mar. 16, 2020, the entire contents of that application beingincorporated herein by reference.

FIELD OF THE INVENTION

The presently disclosed subject matter relates generally to methods anddevices for transcranial illumination for the therapeutic treatment ofneurological conditions. Preferred embodiments can include wearabledevices that communicate with mobile devices such as web enabled phonesand tablets to facilitate system operation and patient data analysis.This can optionally include cross-modal brain stimulation, diagnosticmodalities and, more particularly, provide methods and devices fortreating children suffering from autism that can optionally utilizesimultaneous audio and light stimulation.

BACKGROUND

Research indicates that in treating many neurological and psychiatricconditions, a strong combinatory effect of two separate types oftreatments exists. For example, in the treatment of depression andanxiety, a combination of both medications and cognitive behavioraltherapy (or dialectic behavioral therapy) produces stronger effects thaneither one of those modalities independently.

Furthermore, music therapy and videos games have been used to treatepilepsy patients. Some of the results indicate that listening tospecific musical content in combination with pharmacological treatmentreduced both the frequencies of epileptic discharges and frequencies ofseizures. Similarly, combining video games with pharmacologicaltreatment has also been shown to modulate the brain neuroplasticity andimprove age-related neuronal deficits and enhanced cognitive functionsin older adults. Therefore, adding two types of different treatmentstogether has been shown to improve the outcome of the overall treatmentof neurological and psychiatric conditions across various domains.Overall, when treating psychiatric or neurological disorder, combinatoryeffects of brain stimulation through various channels is likely to bestronger than unimodal stimulation.

For children diagnosed with Autism Spectrum Disorder (“ASD”), one of themost common challenges they face is learning language. Studies show thatchildren with ASD struggle with acquiring syntax. As a result, theycannot parse sentences, understand speech, and/or acquire or produce newwords. In particular, learning language by the age of five (being ableto speak full sentences) is critical for future successful integrationwith neuro-typical community and independent functioning. In addition,language learning may only occur during the sensitive period (REFS),which ends between 5-7 years of age. If a child does not fully learnlanguage during that period, subsequent learning is highly effortful andachieving fluency is unlikely. Furthermore, being able to comprehend andproduce language reduces tantrums and improves behavior in individualswith ASD. Therefore, delays in speech development is one of the mostcritical symptoms that needs to be alleviated.

Another critical symptom that needs to be alleviated in children withASD is anxiety. General anxiety is frequently quite debilitating in ASDchildren and it affects, among other things, children’s ability to learnand ability to integrate socially. Children with ASD are frequentlyprescribed medication to reduce their anxiety, but these medicationsoften have unintended side effects and may be not effective.

In the United States, there are over 1.5 MM children currently diagnosedwith ASD, and approximately 80,000 new children are diagnosed with ASDannually. Across the world, approximately 1.5 MM-2 MM new children areannually diagnosed with ASD. Autism services cost Americansapproximately $250 billion a year, which includes both medical costs(outpatient care, home care, and drugs) and non-medical costs (specialeducation services, residential services, etc.). In addition to outrightcosts, there are hidden ones, such as emotional stress as well as thetime required to figure out and coordinate care. Research indicates thatlifelong care costs can be reduced by almost two thirds with properearly intervention.

Further research indicates that ASD is often correlated withmitochondrial dysfunction. Mitochondria in brain cells of autisticindividuals does not produce enough adenosine triphosphate (“ATP”). Theresult of mitochondria dysfunction may be especially pronounced in thebrain, since it uses 20% of all the energy generated by the human body,which may lead to neuro-developmental disorders, such as ASD.Encouraging research has shown that infrared and red light may activatea child’s mitochondria, and therefore increase ATP production.

Transcranial photobiomodulation (“tPBM”) of the brain with near infraredand red light has been shown to be beneficial for treating variouspsychiatric and neurological conditions such as anxiety, stroke andtraumatic brain injury. Remarkably, autism spectrum disorder maypotentially be treated therapeutically with tPBM as several scientistshave recently linked the disorder to mitochondria disbalance and tPBMcan potentially affect mitochondria by causing it to produce more ATP.Patients treated with tPBM will absorb near infrared light, which canpotentially reduce inflammation, increase oxygen flow to the brain andincrease production of ATP. However, devices and methods are needed thatwill enable additional treatment options for various neurologicalconditions.

One problem with language acquisition is that many children with ASDcannot focus on the language enough to extract syntactic features ofwords, to parse sentences, and/or to attend to syntactic and semanticclues of speech. Therefore, their word learning may be delayed.

The problem with anxiety is that ASD children frequently get verystressed and do not know how to calm themselves before a particularlearning or social situation. As a result, they are unable toparticipate in regular activities (such as playdates or classes).

Accordingly, there is a need for improved methods and devices providingtreatment of neurological disorders and to specifically providetherapies for the treatment of children.

SUMMARY

Preferred embodiments provide devices and methods in which a headwearable device is configured to be worn by a subject that is operatedto deliver illuminating wavelengths of light with sufficient energy thatare absorbed by a region of brain tissue during a therapeutic period.Transcranial delivery of illuminating light can be performed with aplurality of light emitting devices mounted to the head wearable devicethat can also preferably include control and processing circuitry.Therefore, providing brain stimulation with one or more of, orcombinations of (i) infrared, near infrared and red light to improveoperational states of the brain such as by ATP production in the brain,for example, and (ii) provide additional specific linguistic input(s) tolearn syntax will improve language acquisition in ASD children.Therefore, providing brain stimulation with a combination of (i) nearinfrared and red light to reduce anxiety and (ii) specific meditationswritten for ASD children will reduce anxiety. Reduced anxiety leads toboth improved language learning and better social integration. Providingan audio language program specifically designed for ASD children, mayfocus the attention of the child on the language, provide the child withthe information about linguistic markers, and improve the child’sability to communicate. This is likely to reduce lifelong care costs foraffected individuals.

Preferred embodiments can use a plurality of laser diodes or lightemitting diodes (LEDs) configured to emit sufficient power through thecranium of a patient to provide a therapeutic dose during a therapeuticperiod. This plurality of light emitting devices can be mounted tocircuit boards situated on a head wearable device. For the treatment ofchildren the spacing between light emitters in each array mounted to thehead wearable device can be selected to improve penetration depththrough the cranium. As the cranium of a child increases in thicknesswith age, the parameters of light used to penetrate the cranium willchange as a function of age. As attenuation of the illuminating lightwill increase with age, the frequency of light, power density and spotsize of each light emitter can be selectively adjusted as a function ofage. The system can automatically set the illumination conditions as afunction of age of the patient. The thickness of the cranium of anindividual patient can also be quantitatively measured by x-ray scan andentered into the system to set the desired illumination parametersneeded to deliver the required power density to the selected region ofthe brain. The density of the cranium can also change as a function ofage and can be quantitatively measured by x-ray bone densitometer togenerate further data that can be used to control and adjust the levelof radiance applied to different regions of the cranium.

Aspects of the disclosed technology include methods and devices forcross-modal stimulation brain stimulation, which may be used to treatASD children. Consistent with the disclosed embodiments, the systems andmethods of their use may include a wearable device (e.g., a bandana)that includes one or more processors, transceivers, microphones,headphones, LED lights (diodes), or power sources (e.g., batteries). Oneexemplary method may include positioning the wearable device on the headof a patient (an ASD child). The method may further includetransmitting, by the wearable device (e.g., the LED lights), apre-defined amount of light (e.g., red or near infrared light). Themethod may also include simultaneously outputting, by the headphones ofthe wearable device or other device that can be heard or seen by thepatient, a linguistic input to the patient, for example. The linguisticinput may include transparent syntactic structures that facilitate, forexample, learning how to parse sentences. Also, the method may includeoutputting specific meditations written for ASD children, that may helpease anxiety, and thus allowing ASD children to better learn languageand more easily integrate socially. In some examples, the method mayfurther include receiving a response to the linguistic input from thepatient, that the one or more processors may analyze to determine theaccuracy of the response and/or to generate any follow-up linguisticinputs. Further, in some examples, the frequency and/or type of lightoutputted by the wearable device may be adjusted based on the responsereceived from the patient. Also, in some examples, the wearable devicemay be paired to a user device (e.g., via Bluetooth®) that determinesand sends the linguistic input(s) to the wearable device or otherdevices including one or more transducer devices, such as speakers, ordisplay devices that can generate auditory or visual signals/images thatcan be heard and/or seen by the patient.

The head wearable device can comprise rigid, semi-rigid or flexiblesubstrates on which the light emitters and circuit elements areattached. The flexible substrates can include woven fabrics or polymerfibers, molded plastics or machine printed components assembled into aband that extends around the head of the patient. Circuit boards onwhich electrical and optical components are mounted and interconnectedcan be standard rigid form or they can be flexible so as to accommodatebending around the curvature of the patient’s head. As children andadults have heads in a range of different sizes, it is advantageous tohave a conformable material that can adjust to different sizes. Morerigid head wearable devices can use foam material to provide aconformable material in contact with the patient’s head. The headwearable device can be used in conjunction with diagnostic devices andsystems that can be used to select the parameters for the therapeuticuse of light as described herein. A computing device such as a tablet orlaptop computer can be used to control diagnostic and therapeuticoperations of the head worn device and other devices used in conjunctionwith a therapeutic session. Such computing devices can store and managepatient data and generate electronic health or medical records forstorage and further use. The computing device can be programmed withsoftware modules such as a patient data entry module, a system operatingmodule that can include diagnostic and therapeutic submodules, and anelectronic medical records module. The system can include a networkedserver to enable communication with remote devices, web/internetoperations and remote monitoring and control by secure communicationlinks. The computing device can include connections toelectroencephalogram (EEG) electrodes to monitor brain activity before,during or after therapeutic sessions to generate diagnostic data for thepatient. The EEG electrodes can be integrated with the head wearabledevice and be connected either directly to a processor thereon, oralternatively, can communicate by wired or wireless connection to theexternal computing device such as a touchscreen operated tablet displaydevice. Light sensors that are optically coupled to the head of thepatient can be used to monitor light delivery into the cranium of thepatient and/or can measure light returning from the regions of the brainthat receive the illuminating light. An array of near infrared sensorscan be mounted on the LED panels or circuit boards, for example, thatcan detect reflected light or other light signals returning from thetissue that can be used to diagnose a condition of the tissue.Diagnostic data generated by the system sensors can be used to monitorthe patient during a therapeutic period and can optionally be used tocontrol operating parameters of the system during the therapy sessionsuch as by increasing or decreasing the intensity of the light deliveredthrough the cranium or adjusting the time period or areas of the brainbeing illuminated during the therapy session.

Further features of the disclosed design, and the advantages offeredthereby, are explained in greater detail hereinafter with reference tospecific embodiments illustrated in the accompanying drawings, whereinlike elements are indicated be like reference designators.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, are incorporated into and constitute aportion of this disclosure, illustrate various implementations andaspects of the disclosed technology, and, together with the description,serve to explain the principles of the disclosed technology. In thedrawings:

FIG. 1 is an example head wearable device, in accordance with someexamples of the present disclosure.

FIGS. 2A-2C show rear, side and front views of a patient with the headwearable device of FIG. 1 .

FIG. 3 illustrates use of a portable phone or tablet device connected tothe head wearable device.

FIG. 4 schematically illustrates the operating elements of the headwearable device and control features.

FIG. 5 schematically illustrates the components of a head wearabledevice in accordance with preferred embodiments.

FIG. 6 illustrates a screen shot of a testing procedure used withpreferred embodiments of the invention.

FIG. 7 illustrates a light emitter for transcranial illumination mountedon one side of a circuit board that is mounted to the head wearabledevice.

FIG. 8 illustrates a second side of the circuit board shown in FIG. 7including connectors to the controller and power source for the headwearable device.

FIG. 9 illustrates a detailed view showing circuit board elements of thehead wearable device of certain embodiments.

FIG. 10 shows circuitry mounted on a circuit board of the head wearabledevice for preferred embodiments.

FIG. 11 shows circuitry mounted on a circuit board for control ofpreferred embodiments of a head wearable device.

FIG. 12 shows circuitry mounted on a circuit board to control operationsof the head wearable device.

FIG. 13A is a process flow diagram in accordance with preferred methodsof operating the head wearable device and control system.

FIG. 13B depicts a diagram of a battery discharge curve.

FIG. 13C depicts a diagram of relative output flux vs. forward current.

FIG. 13D depicts a diagram of relative voltage vs. forward current.

FIG. 13E depicts a diagram of relative output flux vs. temperature.

FIG. 13F depicts a battery discharge curve.

FIG. 14 is a process flow diagram illustrating the use of EEGmeasurements in conjunction with transcranial illumination of a patient.

FIG. 15 illustrates a table with exemplary parameters having variableranges between upper and lower thresholds used for transcranialillumination of a patient in accordance with preferred embodiments.

FIG. 16 illustrates a process flow diagram for selecting and optimizingparameters over multiple therapeutic sessions including manual andautomated selection tracks.

FIG. 17 illustrates a process flow diagram for administering atherapeutic session to a patient in accordance with various embodimentsdescribed herein.

FIG. 18 illustrates a further view of a head worn device having circuithousing elements accessible to a user that is communicably connected toa first tablet device used by the patient during a therapy session and asecond tablet used by an operator to monitor, control and/or program thesystem for diagnostic and therapeutic use as described generally herein.

DETAILED DESCRIPTION

Some implementations of the disclosed technology will be described morefully with reference to the accompanying drawings. This disclosedtechnology can be embodied in many different forms, however, and shouldnot be construed as limited to the implementations set forth herein. Thecomponents described hereinafter as making up various elements of thedisclosed technology are intended to be illustrative and notrestrictive. Many suitable components that would perform the same orsimilar functions as components described herein are intended to beembraced within the scope of the disclosed electronic devices andmethods. Such other components not described herein can include, but arenot limited to, for example, components developed after development ofthe disclosed technology.

It is also to be understood that the mention of one or more method stepsdoes not imply that the methods steps must be performed in a particularorder or preclude the presence of additional method steps or interveningmethod steps between the steps expressly identified.

Reference will now be made in detail to exemplary embodiments of thedisclosed technology, examples of which are illustrated in theaccompanying drawings and disclosed herein. Wherever convenient, thesame references numbers will be used throughout the drawings to refer tothe same or like parts.

FIG. 1 shows an example wearable device 50 that may implement certainmethods for cross-modal brain stimulation. As shown in FIG. 1 , in someimplementations the wearable device 50 may include one or moreprocessors, transceivers, microphones, headphones 52, LED lights 54,and/or batteries, amongst other things. The wearable device 50 may bepaired with a user device (e.g., smartphone, smartwatch), which mayprovide instructions that may determine a frequency of transmittedlight, the type of light (e.g., red light or infrared light), themeditations, and/or the linguistic inputs. FIGS. 2A-2C depict rear sideand front views of the head wearable device 50 positioned on the head ofa patient with rear circuit board 56, side illumination panels 56, andfront illumination panel 62 to provide transcranial illumination, andalso earphones 52 to provide audio programming to the patient. Thesystem can store audio files or video files that can be heard or seen bythe user in conjunction with the therapeutic session for a patient.

FIG. 3 is an illustration of a system 100 for brain stimulation inaccordance with various embodiments described herein. The system 100includes a photobiomodulation device 110 in communication with a remotecomputing device 150. In exemplary embodiments, the computing device 150includes a visual display device 152 that can display a graphical userinterface (GUI) 160. The GUI 160 includes an information display area162 and user-actuatable controls 164. Optionally, the computing device150 is also in communication with an external EEG system 120′.Optionally, the computing device 150 is also in communication with anexternal light sensor array 122′. An operating user can operate thecomputing device 150 to control operation of the photobiomodulationdevice 110 including activation of the functions of thephotobiomodulation device 110 and mono- or bi-directional data transferbetween the computing device 150 and the photobiomodulation device 110.

The operating user can change among operational modes of the computingdevice 150 by interacting with the user-actuatable controls 164 of theGUI 160. Examples of user-actuatable controls include controls to accessprogram control tools, stored data and/or stored data manipulation andvisualization tools, audio program tools, assessment tools, and anyother suitable control modes or tools known to one of ordinary skill inthe art. Upon activation of the program control mode, the GUI 160displays program control information in the information display area162. Likewise, activation of other modes using user-actuatable controls164 can cause the GUI 160 to display relevant mode information in theinformation display area 162. The system can be programmed to performtherapeutic sessions with variable lengths of between 5 and 30 minutes,for example. The patient’s use of language during the session can berecorded by microphone on the head wearable device or used separatelyand an analysis of language used during the session or stored for lateranalysis.

In the program control mode, the GUI 160 can display program controlsincluding one or more presets 165. Activation of the preset by theoperating user configures the photobiomodulation device 110 to usespecific pre-set variables appropriate to light therapy for a particularclass of patients or to a specific patient. For example, a specificpreset 165 can correspond to a class of patient having a particular ageor particular condition. In various embodiments, the pre-set variablesthat are configured through the preset 165 can include illuminationpatterns (e.g., spatial patterns, temporal patterns, or both spatial andtemporal patterns), illumination wavelengths/frequencies, orillumination power levels.

In some embodiments, the photobiomodulation device 110 can transmitand/or receive data from the computing device 150. For example, thephotobiomodulation device 110 can transmit data to log information abouta therapy session for a patient. Such data can include, for example,illumination patterns, total length of time, time spent in differentphases of a therapy program, electroencephalogram (EEG) readings, andpower levels used. The data can be transmitted and logged before,during, and after a therapy session. Similar data can also be receivedat the computing device 150 from the external EEG system 120′ or theexternal light sensor array 122′ in embodiments that utilize thesecomponents. In the stored data manipulation and/or visualization mode,the operating user can review the data logged from these sources andreceived at the computing device 150. In some embodiments, the data caninclude information regarding activities used in conjunction with thetherapy session (i.e., information related to tasks presented to thepatient during the therapy session such as task identity and scoring).For example, activity data can be input by an operating user on theassessment mode screen as described in greater detail below.

In the audio system mode, the user can control audio information to bedelivered to the patient through speakers 116 of the photobiomodulationdevice 110. Audio information can include instructions to the patient insome embodiments. In other embodiments, audio information can includeaudio programming for different therapeutic applications.

In the assessment mode, a user can input or review data related topatient assessment such as task identity and scoring. For example, FIG.6 illustrates a particular assessment test displayed in the informationdisplay area 162 of the GUI 160. This assessment test, the Weekly ChildTest, includes rating scales representing scoring on a variety ofindividual metrics geared to an overall assessment of the severity ofautism in the child.

As described in greater detail below, the computing device 150 andphotobiomodulation device 110 can communicate through a variety ofmethods. In some embodiments, a direct (i.e., wired) connection 117 canbe established between the computing device 150 and thephotobiomodulation device 110. In some embodiments, the computing device150 and the photobiomodulation device 110 can communicate directly withone another through a wireless connection 118. In still furtherembodiments, the computing device 150 and the photobiomodulation device110 can communication through a communications network 505.

In various embodiments, one or more portions of the communicationsnetwork 505 can be an ad hoc network, a mesh network, an intranet, anextranet, a virtual private network (VPN), a local area network (LAN), awireless LAN (WLAN), a wide area network (WAN), a wireless wide areanetwork (WWAN), a metropolitan area network (MAN), a portion of theInternet, a portion of the Public Switched Telephone Network (PSTN), acellular telephone network, a wireless network, a Wi-Fi network, a WiMAXnetwork, an Internet-of-Things (IoT) network established usingBluetooth® or any other protocol, any other type of network, or acombination of two or more such networks.

In exemplary embodiments, the system 100 is configured to treat autisticpatients and, in particular, juvenile autistic patients. As such, it isdesirable in many embodiments to create a wireless connection betweenthe photobiomodulation device 110 and the computing device 150 as ajuvenile patient is less likely to sit still for the length of a therapysession. Wireless connection and use of a battery to power thephotobiomodulation device 110 enables uninterrupted transcranialillumination for the entire length of a single therapy session and,further, enables the juvenile patient to move and engage in activitiesthat may, or may not, be associated with the therapy.

FIG. 4 shows block diagrams of a remote computing device 150 andphotobiomodulation device 110 suitable for use with exemplaryembodiments of the present disclosure. The remote computing device 150may be, but is not limited to, a smartphone, laptop, tablet, desktopcomputer, server, or network appliance. The remote computing device 150includes one or more non-transitory computer-readable media for storingone or more computer-executable instructions or software forimplementing exemplary embodiments. The non-transitory computer-readablemedia may include, but are not limited to, one or more types of hardwarememory, non-transitory tangible media (for example, one or more magneticstorage disks, one or more optical disks, one or more flash drives, oneor more solid state disks), and the like. For example, memory 156included in the remote computing device 150 may store computer-readableand computer-executable instructions or software for implementingexemplary operations of the remote computing device 150. The remotecomputing device 150 also includes configurable and/or programmableprocessor 155 and associated core(s) 404, and optionally, one or moreadditional configurable and/or programmable processor(s) 402′ andassociated core(s) 404′ (for example, in the case of computer systemshaving multiple processors/cores), for executing computer-readable andcomputer-executable instructions or software stored in the memory 156and other programs for implementing exemplary embodiments of the presentdisclosure. Processor 155 and processor(s) 402′ may each be a singlecore processor or multiple core (404 and 404′) processor. Either or bothof processor 155 and processor(s) 402′ may be configured to execute oneor more of the instructions described in connection with remotecomputing device 150.

Virtualization may be employed in the remote computing device 150 sothat infrastructure and resources in the remote computing device 150 maybe shared dynamically. A virtual machine 412 may be provided to handle aprocess running on multiple processors so that the process appears to beusing only one computing resource rather than multiple computingresources. Multiple virtual machines may also be used with oneprocessor.

Memory 156 may include a computer system memory or random access memory,such as DRAM, SRAM, EDO RAM, and the like. Memory 156 may include othertypes of memory as well, or combinations thereof.

A user may interact with the remote computing device 150 through avisual display device 152, such as a computer monitor, which may displayone or more graphical user interfaces 160. In exemplary embodiments, thevisual display device includes a multi-point touch interface 420 (e.g.,touchscreen) that can receive tactile input from an operating user. Theoperating user may interact with the remote computing device 150 usingthe multi-point touch interface 420 or a pointing device 418.

The remote computing device 150 may also interact with one or morecomputer storage devices or databases 401, such as a hard-drive, CD-ROM,or other computer readable media, for storing data and computer-readableinstructions and/or software that implement exemplary embodiments of thepresent disclosure (e.g., applications). For example, exemplary storagedevice 401 can include modules to execute aspects of the GUI 160 orcontrol presets, audio programs, activity data, or assessment data. Thedatabase(s) 401 may be updated manually or automatically at any suitabletime to add, delete, and/or update one or more data items in thedatabases. The remote computing device 150 can send data to or receivedata from the database 401 including, for example, patient data, programdata, or computer-executable instructions.

The remote computing device 150 can include a communications interface154 configured to interface via one or more network devices with one ormore networks, for example, Local Area Network (LAN), Wide Area Network(WAN) or the Internet through a variety of connections including, butnot limited to, standard telephone lines, LAN or WAN links (for example,802.11, T1, T3, 56kb, X.25), broadband connections (for example, ISDN,Frame Relay, ATM), wireless connections (for example, WiFi orBluetooth®), controller area network (CAN), or some combination of anyor all of the above. In exemplary embodiments, the remote computingdevice 150 can include one or more antennas to facilitate wirelesscommunication (e.g., via the network interface) between the remotecomputing device 150 and a network and/or between the remote computingdevice 150 and the photobiomodulation device 100. The communicationsinterface 154 may include a built-in network adapter, network interfacecard, PCMCIA network card, card bus network adapter, wireless networkadapter, USB network adapter, modem or any other device suitable forinterfacing the remote computing device 150 to any type of networkcapable of communication and performing the operations described herein.

The remote computing device 150 may run operating system 410, such asversions of the Microsoft® Windows® operating systems, differentreleases of the Unix and Linux operating systems, versions of the MacOS®for Macintosh computers, embedded operating systems, real-time operatingsystems, open source operating systems, proprietary operating systems,or other operating system capable of running on the remote computingdevice 150 and performing the operations described herein. In exemplaryembodiments, the operating system 410 may be run in native mode oremulated mode. In an exemplary embodiment, the operating system 410 maybe run on one or more cloud machine instances.

The photobiomodulation device 110 can include a processor board 111, oneor more light emitter panels 115 a-115 e, one or more speakers 116, andone or more batteries 118. The photobiomodulation device 110 canoptionally include a light sensor array 122 and an EEG sensor system120. Although five light emitter panels 115 a-115 e are described withrespect to this disclosure, one or ordinary skill in the art wouldappreciate that a greater or fewer number of panels may be used. In anexemplary embodiment, the light emitter panels 115 a-115 e hareflexible. In an exemplary embodiment, the light emitter panels 115 a-115e are positioned at the front, top, back, and both sides of the user’shead. In embodiments wherein the photobiomodulation device 110 does nothave a full cap over the user’s head (i.e., a headband-style device),the top panel may be omitted.

FIG. 5 illustrates a schematic layout of the photobiomodulation device110 of the present invention. The processor board 111 is, for example, aprinted circuit board including components to control functions of thephotobiomodulation device 110. The processor board 111 can include acentral processing unit 112 and a power management module 114 in someembodiments.

The power management module 114 can monitor and control use ofparticular light emitter panels 115 a-115 e during a therapy session. Insome embodiments, the power management module 114 can take action tocontrol or provide feedback to a patient user related to whether lightemitter panels 115 a-115 e are not used, or are only partially used,during a particular therapy session. By mitigating use of certain panelsduring a session, longer operation can be achieved. Moreover, differentclasses of patient (e.g., patients of different ages) can have differentcranial thicknesses. As a result, different transmission power (andpenetration) may be necessary as a function of patient age. The powermanagement module 114 can control power output to light emitter panelsto provide a therapeutically beneficial dose of illumination while stillextending battery life. Shown in FIG. 7 is an LED 202 mounted on a firstside of a printed circuit board 200 which can have connectors 208 forwiring to the main circuit panel 270 shown in FIG. 12 . The LED 202 canhave a fixed spot size 205 as it enters the cranium of the patient.Alternatively, the spot size can be reduced or increased by selectedamounts to either reduce the volume of brain tissue illuminated, orincrease the volume. The LED panel shown in FIG. 7 can include sensorcomponents such as EEG electrodes and/or photodetectors configured todetect light from the illuminated tissue within the cranium. The circuitpanel 270 can include a wireless transceiver to transmit and receivedata from the external controller within the tablet as described herein.The circuit panel 270 can also include a wired connector to connect thesystem to an external power source and the tablet used to control thesystem. As shown in FIG. 12 , two manual switches 272, 274 can be usedto actuate different power levels of the system. In this specificexample a first switch selects between two different levels and thesecond switch selects among four different settings or sublevels for atotal of eight different options. These switches can also be controlledremotely from a tablet as described herein. An LED 276 is used toindicate to a user that the power is on. A further switch 282 can turnon the wireless transmitter 280, which in this implementation, is aBluetooth transceiver. LEDs 284 can further indicate the status of thetransmitter. A central microprocessor 278 is programmed to controloperations of circuit board 270. The power supply board 250 andcontroller board 260 shown in FIGS. 10 and 11 regulate power from theone or more batteries to the controller board. The on/off power switch262 for the head worn device can be located on board 260 which includesan inductor 264 so that the voltage delivered to the LEDs does not varyas power is drawn from the batteries. These components are mounted onthe head wearable device 110 with earphones 52 which are driven by themain controller board so that the patient can hear audio files usedduring therapeutic sessions. Alternatively, the electronics shown anddescribed herein can be implemented using integrated circuit componentsto reduce size, weight and power requirements. An electronic sensor canmonitor the voltage applied to one or more LEDs so as to record theamount of optical power delivered to the patient. The electronics can beimplemented as an application specific integrated circuit (ASIC) or asystem on chip (SOC) design.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disordercharacterized by diminished social functioning, inattentiveness, andlinguistic impairment. While autism is likely to be a multi-causaldisorder, research indicates that individuals with ASD frequently havemitochondrial disease which results in abnormalities of energygeneration from food proteins. However, mitochondria in the brain mightbe able to produce energy molecules from a different source, such aslight.

Using the wearable device 50, certain methods of the present disclosuremay perform photobiomodulation (stimulating brain with light) andlinguistic training simultaneously to treat children with ASD. Thewearable device 50 may include several near infrared and/or red lightsto stimulate the language area of the brain. These methods associatedwith the wearable device 50 may include determining an area of the headto position the wearable device 50 (e.g., the temporal lobe, theprefrontal cortex, and/or the occipital lobe) to output the infraredand/or red lights. The light absorbed by the brain tissue may increasethe production of ATP, which may provide the neurons more energy tocommunicate with each other and provide increased brain connectedness.The wearable device 50 may simultaneously receive linguistic inputs froman application of a user device that is transmitted to the user via theheadphones of the wearable device 50. The linguistic inputs may helpfacilitate language learning. Therefore, by providing these combinedmechanisms (photobiomodulation and linguistic input), for example, tochildren diagnosed with ASD, may significantly improve lifelongoutcomes. Further, the wearable device 50 may output meditations thatmay help reduce anxiety of the patient user (such as an ASD child),which may allow the user to better learn language and integratesocially.

Methods for providing cross-modal brain stimulation may includedetermining the light frequency, location of the LED lights (e.g., areasof the brain needing increased ATP, areas of the brain most likely torespond to light treatments, and/or areas of the brain associated withlanguage (e.g., auditory cortex, Broca area, Wernike area)), whether ATPproduction increased, and the overall effect of the treatments.Accordingly, based on the determined overall effect on the brain, thewearable device may be dynamically adjusted on a user-specific basis.

The wearable device 50 may be specifically tailored for children withASD, such that it improves language skills, alleviates anxiety, and/orreduces tantrums. Further, the wearable device 50 may be used on a dailybasis, in the convenience of the family’s home, without a need for aspecially trained therapist. Moreover, the wearable device 50 may benon-invasive, may not require a prescription, and/or may lack sideeffects.

Methods for using the devices of the present disclosure may furtherinclude determining the location(s) of the light emitting diodes thatmay be used to stimulate specific brain areas responsible for language,comprehension, energy production, and/or for self-regulation (e.g.,reducing anxiety). The methods may also include determining total power,power density, pulsing, and/or frequency. The total power may be 400-600mW (0.4-0.6 W) with 100-150 mW per each of four panels. The power foreach panel may be selectively stepped down to the 50-100 mW range, orincreased to the 150-200 mW range depending on the age or condition ofthe patient. Each of these ranges may be further incremented in 10 mWsteps during a treatment session or between sessions. The spot size ofthe light generated by each LED or laser can optionally be controlled byadjusting the spacing between the light emission aperture of the LED orby using a movable lens for one or more LEDs on each circuit board thatcan be moved between adjustable positions by a MEMS actuator, forexample.

Further, the wearable device 50 may be comprised of a comfortablematerial for prospective patients. For example, the wearable device maybe comprised of plastic, fabric (e.g., cotton, polyether, rayon, etc.),and/or the like. Because ASD patients in particular are especiallysensitive, the aforementioned materials may be integral in allowing ASDpatients to wear it for a sufficient amount of time without beingirritable. Of course, the wearable device 50 may need to be both safeand comfortable. The electric components (e.g., processors, microphones,headphones, etc.) may be sewn into the wearable device 50 and may bedifficult to reach by children, for example. A cloth or fabric coveringcan contain the head worn frame and optoelectronic components to theextent possible without interfering with the optical coupling of the LEDto the cranium. Further, the weight of the wearable device 100 may belight enough to allow it to be worn comfortably. Moreover, the wearabledevice 100 may require a power source (e.g., one or more replaceablebatteries) that allows it to be portable.

Regarding the linguistic inputs, a patient user device (e.g., asmartphone or tablet) may include an application that 1) performslanguage acquisition: (e.g., develops and records a vast number of shortvignettes specifically designed to make syntactic structure transparentand teaches how to parse sentences); 2) involves a system ofspecifically designed mediations to alleviate anxiety; and 3) involves asystem of musical rewards to keep users (children) interested andengaged.

The application may disambiguate syntactic structure of a language.Present research suggests that word learning spurt occurs after thechildren learn basic syntax (and it occurs at the syntactic-lexiconinterface). Furthermore, without syntax children may not move beyondspeaking 10-15 words, which may be used for simple labeling, but not toexpress their needs, wants and feelings. This means that there may be noability for proper communication without learning syntax first. Inaddition, syntax may be necessary to parse the acoustic wave or soundthat children hear into sentences and words. Syntax may also benecessary for specific word-learning strategies (e.g., syntacticbootstrapping).

Syntactic bootstrapping is a mechanism which children use to infermeanings of verbs from the syntactic clues. For example, when a childhears “Michael eats soup” this child infers that “eats” is a transitiveverb. A classic example used by a famous psycholinguist professor LeilaGleitman is the made-up verb “Derk”. By putting this verb in severalsyntactic contexts, the meaning of the verb becomes transparent “Derk!Derk up! Derk here! Derk at me! Derk what you did!” Dr. Gleitman arguedthat children infer the meanings of verbs from hearing them in differentsyntactic contexts. In addition, Dr. Pinker argued that children alsouse semantic bootstrapping (contextual clues) to infer meanings of thewords. Therefore, there are several mechanisms (most likely innate)available to a typical child while learning language. Overall, there isscientific consensus that typical children learn language byspecifically focusing on syntactic and semantic clues of speech.

However, studies suggest that children who are on the autism spectrumcannot always extract syntactic structure and semantic contexts from theimperfect linguistic input they receive. Usual linguistic input is toomessy, incomplete and confusing for them. People frequently speak infragments of sentences, switch between topics, use incorrect words oruse words in incorrect forms. Human speech may be too messy to allow forsimple learning based on this type of speech alone. Neurotypicalchildren can still extract syntactic structure from this messy input bybeing predisposed to pay attention to specific syntactic cues (e.g., tolook for nouns and verbs in the string of speech). When children graspsyntactic structure of a language, they learn to parse sentences, andtherefore, acquire more words. Several studies corroborated thishypothesis that massive word learning happens at this syntax-lexiconinterface, including studies with children on the spectrum.

Many children suffering from ASD seem to be unable to move beyond simplelabeling, are unable to speak in full sentences, and therefore areunable to communicate effectively. There are many reasons for thisdifficulty, one of them is that those children do not usually pay enoughattention to speech and communication, and therefore they do not payenough attention to syntactic clues and are not able to parse individualsentences. However, without grasping syntactic structure of thelanguage, word learning beyond simple labeling becomes impossible,specifically, acquisition of verbs may become impossible. Timelyacquisition of verbs (not just nouns to label objects around them) maybe critical for ASD children, as research shows that the best predictorof future integration with the neuro-typical community (and normalfunctioning) is speaking full sentences by 5 years of age. Therefore,specifically, the problem is that children with ASD are not focused onthe language enough to extract syntactic features of words, to parsesentences and to attend to syntactic and semantic clues of speech.Therefore, their word learning is delayed.

Accordingly, the aforementioned application may calibrate the imperfectlinguistic input for ASD children, thus, making syntactic structure astransparent as possible. For example, the child will hear a noun: “dog”,then she will hear “1 dog, 2 dogs, 3 dogs, 4 dogs, 5 dogs”, then shewill hear “my dog is brown”, “ my brown dog is cute”, “ my brown dog issmall”, “I have a small, cute, brown dog”, “my dog barks,” “dogs bark”“dogs chase cats”, “dogs eat meat”, “I have a dog,” and so on. Byputting the same word in different syntactic contexts over and overagain we will flood the child with the information about linguisticmarkers (syntactic roles in the sentences, countable, noun,animate/inanimate and so on).

Therefore, the application may “wake up” (activate) language learningand make a child pay attention to the syntactic cues of the linguisticinput. Further, the application may be refined by observing the behaviorof the users and recording their improvements. A method for treatment450 is described in connection with the process flow diagram of FIG. 13Awherein preset or manually entered parameters 452 can be entered bytouch actuation on the tablet touchscreen so that the system controllercan actuate the illumination sequence. These parameters are stored 454in memory. The software for the system then executes stored instructionsbased on the selected parameters to provide transcranial illumination456 for the therapeutic period. The system can utilize optional audio orvideo files 458 in conjunction with the therapy session. The system thancommunicates the recorded data 460 for the therapeutic session forstorage in the electronic medical record of the patient. The data can beused for further analysis such as by application of a machine learningprogram to provide training data.

The following describes an example of a battery powered system aspreviously described herein where one or two 9 volt batteries areinserted into battery holders in the side and rear views showing the LEDcase design shown in the figures.

If the LED is uncased, a small tube can be used to ensure that itremains centered and held securely in place. This tube can fit through ahole in the foam band for proper location and is ⅜″ outside diameter.The PCB serves as a backing on the foam and allows clearance for theconnecting cable. The same type of construction can be applied to theelectronics mounted area, the battery, and the speakers. Sensors used tomeasure characteristics of the patient during use, such as EEGelectrodes, photodetectors and/or temperature sensors can be mounted tothe circuit boards carrying the LEDs or laser diodes as describedgenerally herein. Detected electrical signals from the sensors can berouted to the controller board and stored in local memory and can alsobe transmitted via wireless transmission to the external tablet deviceso that a user or clinician can monitor the therapeutic session andcontrol changes to the operating parameters of the system during use.

The electronics can comprise three or more separate PCB configurationswith the LED PCB having (6) variations for the associated positions onthe head. There can be two LED PCB boards on each side (front and rear)with at least one illuminating the temporal lobe on each side and atleast one board centered for illuminating the frontal lobe. One or twoboards can conform to one or both of the parietal lobe and the occipitallobe.

The system is fitted on the head of a patient and radiates energy via IRLEDs at 40 Hz into the patient’s head, for example. The IR LEDs aresplit into six boards with each containing one IR LED. The LED utilizedfor preferred embodiments can be the SST-05-IR-B40-K850.

The LED boards can illuminate during the on-time of the 40 Hz signal.The duty cycle of the 40 Hz signal will be equal to the power setting.For example, a power setting of 25% will require a 25% duty cycle forthe 40 Hz.

One or more 9V batteries can be the system’s source of power. A buckconverter reduces the 9V from the battery to 2.5 V for the LEDs. One ormore batteries of different voltages can be employed particularly wheredifferent batteries can be used for the light emitters and powering thecircuitry.

In this section, note the calculation of the LED’s absolute maximumoptical flux output assuming that they are the only components poweredby a single 9V battery.

Table 1 shows the current limits of important components. These currentlimits cannot be violated without the risk of permanent damage to thecomponent.

Device Specification Current Limit (A) Absolute Maximum BatteryDischarge 1.0 Absolute Maximum Buck Converter Current Output 2.5Absolute Maximum IR LED Current 1.0

Conservation of energy dictates that the current sourced by the buckconverter will not be the same as the current sourced by the battery.Equation 1 calculates the current drawn from the battery (I_(BATT)).

$I_{BATT} = \frac{V_{LED\_ PWR} \times I_{LED\_ PWR}}{\eta \times V_{BATT}}$

where V_(LED)__(PWR) is the LED supply voltage (2.5 V), I_(LED)__(PWR)is the buck converter output current, n is the efficiency (minimum of0.85), and V_(BATT) is the battery voltage.

The efficiency of the buck converter changes over the output currentrange. The minimum efficiency is 0.85 at the maximum current of 2.5 A.

Note that the battery voltage is inversely proportional to the batterydraw. For a fixed load, the battery will draw more current as thebattery discharges. Therefore, a minimum battery voltage must bespecified and observed by the system microcontroller to avoid exceedingthe battery’s maximum discharge current. Table 2 demonstrates howbattery current draw increases as the battery discharges. Each batterydraw value is calculated with Equation 1 with the following values:η=0.85, V_(LED_) _(PWR)=2.5 V, I_(LED_) _(PWR)=2.5 A, and the batteryvoltage for V_(BATT).

Scenario Battery Draw (mA) Fully Charged Battery at 9 V 816 IntermediateCharge at 7.5 V 980 Absolute Minimum Battery Voltage, 7.35 V 1000

Use Equation 2 to calculate the absolute minimum battery voltage,V_(B_AM). Use the same values as before, but let I_(B_) _(MAX)=1.Battery current draw reaches 1.0 A when the battery voltage dischargesto 7.35 V, therefore the LEDs must be turned off to avoid exceeding theL522 battery maximum discharge specification of 1.0 A. The buckconverter supplying 2.5 A at 2.5 V with a battery voltage below 7.35 Vrisks permanent damage to the battery.

$V_{B\_ AM} = \frac{V_{LED\_ PWR} \times I_{LED\_ PWR}}{\eta \times I_{B\_ MAX}}$

Equation 2. Absolute Minimum Battery Current Draw

The absolute minimum battery voltage also affects battery life. FIG. 13Billustrates a discharge curve for the (Energizer L522) battery and itdemonstrates that a lower absolute minimum battery voltage prolongsbattery life. With a 7.35 V absolute minimum battery voltage, the LEDscan be safely powered for approximately 24 minutes (if the battery wasdrawing 500mA instead of 1.0 A). Thus, a lower absolute minimum batteryvoltage is beneficial.

The 2.5 A sourced by the buck converter must be shared amongst sixboards (LED). Thus 2.5 A / 6 = 416 mA from the buck converter per LED.

FIG. 13C illustrates the manufacturer’s graph of optical flux normalizedat 350 mA. The manufacturer datasheet states that the optical flux at350 mA ranges between 265 mW and 295 mW. At 416 mA, the optical flux isapproximately 110% the optical flux at 350 mA. Using the worst-case fluxoutput of 265 mA, the optical flux at 416 mA is 265 mW × 1.1 = 291.5 mWor approximately 292 mW.

The duty cycle of the 40 Hz will attenuate the optical flux. Equation 3shows how to calculate the average flux for a single pulsed LED.E_(e_pulse) is the optical flux during the pulse and D_(40HZ) is the 40Hz duty cycle. The range of D_(40HZ) is a number between 0 and 1inclusive.

E_(e_average) = D_(40HZ) × E_(e_pulse)

Equation 3 Average Irradiance for a Single LED

As an example, Table 3 lists the optical flux for each power setting.

TABLE 3 Power Settings at Maximum System Power Power Setting OpticalFlux Output (mW) 2% 5.84 4% 11.68 6% 17.52 8% 23.36 16% 46.72 25% 73 50%146 100% 292

The output optical flux decreases with temperature and must be de-ratedaccordingly. Sources of heat to take into account are the LEDs′self-heating and the heat from the patient’s head. For the purposes ofthis analysis, assume the patient’s head is at body temperature, 37° C.

TABLE 4 Temperature Related Coefficients Parameter Value TemperatureCoefficient of Radiometric Power -0.3 %/°C Electrical Thermal Resistance9.2° C./W

Table 4 above lists two thermal coefficients. The thermal resistance ofthe LED can be understood as for every watt consumed by the LED, itstemperature will rise by 9.2° C. The third graph below shows normalizedV-I characteristics of the LED relative to 350 mA at 2 V (at 350 mA,forward voltage ranges between 1.2 V and 2.0 V, but here we continue touse worst-case value of 2.0 V).

At 416mA (the maximum current available per LED), FIG. 13D illustratesthat the forward voltage is approximately 2 V + 0.04 V = 2.04 V. UsingEquation 4, the temperature rise due to self-heating is 7.8° C. at a100% 40 Hz duty cycle.

T_(Δ_(LED)) = V_(f) × I_(f) × D_(40HZ) × 9.2

Equation 4. Temperature Rise Due to Self-Heating

The LED can rise to a temperature of T_(LED) = 37° C. + 7.8° C. = 44.8°C. The optical flux vs temperature graph depicted in FIG. 13E isnormalized to 25° C. Using the temperature coefficient of radiant powerfrom Table 4 and Equation 5, the change in radiant power due totemperature is -5.94%. Therefore, de-rating the worst-case optical fluxof 292 mW derived above by 5.94% yields approximately 275 mW.

$PO_{\Delta\%} = \left( {T_{LED} - 25{^\circ}\text{C}} \right) \times \left( \frac{- 0.3^{\%}}{{^\circ}\text{C}} \right)$

Equation 5 Change in Output Flux Due to Temperature

Note that the system also provides a temperature coefficient for forwardvoltage. Forward voltage decreases with temperature rise. For aworst-case analysis, the decrease in forward voltage due to temperaturecan be ignored.

An optical flux of 275 mW is the minimum absolute maximum that can beachieved if the buck converter and the battery are pushed to theirlimits assuming that the battery is only supplying power to the LEDs.

Since the battery may also be powering the digital logic which includesthe microcontroller, the Bluetooth module or other wireless connection,etc. the LEDs cannot draw the 1.0 A maximum from the battery.

The steps below are an effort to summarize the approach described above.

-   1. Start by selecting the target current for a single LED, I_(f.)-   2. The current sourced by the buck converter will be I_(LED)__(PWR)=    6 × I_(f). If I_(LED_PWR) exceeds 2.5 A, you must decrease I_(f.)-   3. Use Equation 2 to calculate the minimum safe battery voltage to    ensure desired battery life and safe operating conditions. For    efficiency, either use the worst-case value of 0.85 or select the    closest efficiency for your value of I_(LED_PWR) from Table 5.

TABLE 5 Buck Converter Efficiency for Different Output Currents BuckConverter Output, I_(LED)__(PWR) (A) Efficiency, η 2.5 0.85 2.0 0.8711.5 0.89 1.0 0.91 0.5 0.926 0.25 0.91 0.125 0.88

-   4. Use graph to approximate the optical flux output at I_(f.)    -   a. Note: Graph is normalized to optical flux of 265 mW at 350        mA.-   5. Use graph to approximate the forward voltage at I_(f.)    -   a. Note: Graph is normalized to 2.0 V forward voltage at 350 mA.-   6. Calculate the self-heating temperature rise, T_(Δ­_LED), using    Equation 4. Use D_(40 Hz)=1 for 100% 40 Hz duty cycle as the    worst-case temperature rise.-   7. De-rate the optical flux for a T_(Δ_LED) rise over ambient    temperature. Use 37° C. for ambient temperature. This de-rated    optical flux is the maximum flux output for a single LED.

Table 6 gives examples of target LED current and the resulting systemspecification. Allow a 100 mA margin on the battery draw for supplylogic. Values calculated in Table 6 assume worst-case efficiency of0.85.

TABLE 6 LED Current Target Examples Target LED Current (mA) AbsoluteMinimum Battery Voltage (V) Battery Draw at 6.5 V (mA) LED TemperatureRise (°C) Flux Output per LED (mW) Flux Output per LED (temperatureadjusted) (mW) 100 1.765 271 1.7 57 55 200 3.529 543 3.5 133 127 3005.294 814 5.4 207 196 339 5.982 900 6.2 236 223

The maximum target LED current is 339 mA resulting in a temperatureadjusted flux output of 223 mW. Table 7 demonstrates how the 40 Hz dutycycle attenuates the LED output flux.

TABLE 7 Power Settings for Realistically Maximizing Flux Output PowerSetting Optical Flux Output (mW) 2% 4.46 4% 8.92 6% 13.4 8% 17.8 16%35.7 25% 55.8 50% 111.5 100% 223

EEG can be used to augment the use of TPBM to reduce symptoms of autism,for example, and this procedure is described in further detail below.

The head wearable device reduces symptoms of autism by applying tPBM tostabilize functional brain connectivity, while using EEG data as ameasure of the efficacy of tPBM and as a guide for continuousapplications. The head wearable device can include EEG electrodessituated on one or more of the light emitter printed circuit boards asdescribed herein. Between one and six EEG electrodes can be mounted onone or more of the light emitter panels so that they are interleavedbetween the light emitters or surround them so as to detect brain wavesignals occurring during illumination.

Autism (ASD) is a life-long disorder characterized by repetitivebehaviors and deficiencies in verbal and non-verbal communication.Resent research identified early bio-markers of autism, includingabnormalities in EEG of ASD infants, toddlers and children as comparedto typical children. For example, children diagnosed with ASD presentwith significantly more epileptiforms (even, when they do not developseizures), some researchers report as many as 30% of ASD childrenpresent with epileptiforms (e.g., Spence and Schneider, PediatricResearch 65, 599-606 (2009). A recent longitudinal study (from 3 to 36months) detected abnormal developmental trajectory in delta and gammafrequencies, which allow distinguishing children with ASD diagnosis fromothers (Gabard-Durnam et al 2019). Short-range hyper-connectivity isalso reported in ASD children. For example, Orekhova et al (2014),showed that alpha range hyper-connectivity in the frontal area at 14months (and that it correlates with repetitive behaviors at 3 yearsold). Wang et al (2013), has indicated that individuals with ASD presentwith abnormal distribution of various brain waves. Specifically, theresearchers argued that individuals with ASD show an excess powerdisplayed in low-frequency (delta, theta) and high-frequency (beta,gamma) bands, and reduced relative and absolute power in middle-range(alpha) frequencies across many brain regions including the frontal,occipital, parietal, and temporal cortex. This pattern indicates aU-shaped profile of electrophysiological power alterations in ASD inwhich the extremities of the power spectrum are abnormally increased,while power in the middle frequencies is reduced. See FIG. 13F.

Duffy & Als (2019) argued, based on EEG data, that ASD is not a spectrumbut rather a “cluster” disorder (as they identified two separateclusters of ASD population ) and Bosl et al Scientific Reports 8, 6828(2018) used non-linear analyses of infant EEG data to predict autism forbabies as young as 3 months. Further details concerning the applicationof computational methods of Bosl can be found in U.S. Pat. Publication2013/0178731 filed on Mar. 25, 2013 with application number 13/816,645,from PCT/US2011/047561 filed on Aug. 12, 2011, the entire contents ofwhich is incorporated herein by reference. This application describesthe application of machine learning and computational techniquesincluding the use of training data stored over time for numerouspatients and conditions that can be used to train the a machine learningsystem for use with the methods and devices described herein. A neuralnetwork can be used for example to tune the parameters employed fortranscranial illumination of a child at a certain age range undergoingtreatment for autism. An array of 32 or 64 EEG channels can be used withelectrodes distributed around the cranium of the child. Overall, theconsensus is that ASD is a functional disconnectivity disorder, whichhas electrophysiological markers, which can be detected through an EEGsystem. Dickinson et al (2017) showed that at a group level, peak alphafrequency was decreased in ASD compared to TD children.

Transcranial photobiomodulation as described herein is used to treatmany neurological conditions (TBI, Alzheimer, Depression, Anxiety), andis uniquely beneficial to autism, as it increases functionalconnectivity AND affects brain oscillations (Zombordi, et al, 2019; Wanget al 2018). Specifically, Zomorrodi et al Scientific Reports 9(1) 6309(2019) showed that applying tPBM (LED-based device) to Default ModeNetwork increases a power of alpha, beta and gamma, while reduces thepower of delta and theta (at resting state). Wang et al (2018) alsoshowed significant increases in alpha and beta bands. Finally, Pruitt etall (2019) showed that tPBM increases cerebral metabolism of human brain(increasing ATP production).

Thus, preferred embodiments use a system that correlates continuouslycollected EEG data with observable symptoms (as reported by the parents)and use EEG to guide application of LED based tPBM. The symptomsprovided by parents can provide ranked data can be used to formulate theparameters for a therapy session.

LED based tPBM can be applied to Default Mode Network (avoiding centralmidline areas) as well as Occipital lobe, and Broca area (left parietallobe) as well as Wernike area (left temporal lobe).

Stimulating DMN (and simultaneous stimulation of frontal lobe withoccipital lobe) increases long-range coherence. Stimulating languageproducing areas (e.g., Broca and Wernike areas with DMN) has been shownto facilitate language production in aphasic stroke patients (Naeser,2014).

The device will:

-   1. Analyze initial EEG data for epileptiforms, long-range coherence    and hemispheric dominance.-   2. Correlate EEG data with observed symptoms.-   3. Based on the observed symptoms and the EEG data, the head    wearable device can apply tPBM. For example, for children with    severe repetitive behaviors and strong delta and theta power in the    prefrontal cortex, the device stimulates prefrontal cortex to    increase power within alpha and beta frequency band (and decrease    power of delta and theta bands). For children who struggle with    language, the device can stimulate DMN and Broca and Wernike areas.    For children with various and severe symptoms, the device can    stimulate all identified targeted areas (DMN, Broca, Wernike,    occipital lobes).-   4. The device can adjust power gradually and increasing it until the    minimal change in brain oscillation is detected. This thresholding    avoids applying too much power to a developing brain. The device    operates at the lowest power that achieves the desired oscillation.-   5. As the symptoms improve and the measured EEG signal stabilizes,    the power level of the device can be gradually reduced. This system    can be automated to control each therapy session.-   6. Machine learning algorithms analyze EEG data and behavioral data,    and the power alterations provided by the algorithm in the form of    guidance to parents (and therapists), as well as indicate further    improvements in the therapy being given to the patient.-   7. As the symptoms sufficiently improve (expected improvement is    within 8 weeks based on Leisman et al 2018), the device controls a    break from tPBM and collect only EEG and behavioral symptoms to    monitor for possible regression.-   8. If any regress is detected, the device can instruct that tPBM is    gradually resumed.

The device can apply tPBM to DMN, occipital lobe as well as to Broca andWernike areas. The device will collect EEG from prefrontal cortex,occipital cortex and temporal cortex (left and right to monitorhemispheric dominance observed in ASD children). The platform connectedto the device can conduct initial assessment of behavioral symptoms (tobe correlated with EEG data) as well as ongoing collection of symptoms(allowing for continuous correlations with EEG). Therefore the platformwill continuously measure the efficacy of tPBM.

The process flow diagram in FIG. 14 illustrates the method 500 ofperforming transcranial illumination in combination with the use of oneor more sensors to measure characteristics of the brain to monitor thetreatment and detect changes in tissue that indicate a response duringone or more sessions. Preferred embodiments can utilize an EEG sensorarray with the head wearable device to measure brain electric fieldconditions where manual or preset parameters are selected 502 for atherapeutic session. The system performs transcranial illumination 504and data is recorded such as EEG sensor data. Depending on the measureddata and condition of the patient, the system can automatically adjustoperating parameters or they can be manually adjusted 506 by theclinician. The data can be communicated 508 to the computing device suchas the control tablet device and stored in the electronic medical recordof the patient. This can be transmitted by communication networks to ahospital or clinic server for storage and further analysis as describedherein. Shown in FIG. 15 is a table with exemplary values forillumination conditions that can be employed by the system. Theseparameters typically fall within a range of values that the system canuse that extend between a minimum threshold and a maximum threshold.These thresholds can be age dependent as the thickness and density ofthe cranium of a child increase with age as described in Smith et al,“Automated Measurement of Cranial Bone Thickness and Density fromClinical Computed Tomography,” IEEE conference proceedings Eng Med BiolSoc. 2012: 4462-4465 (EMBC 2012), the entire contents of which isincorporated herein by reference. Thus, an age dependent quantitativerating can be associated with each patient that is used to define theillumination parameters used for that patient. Note that different lobesof a child may increase in thickness and/or density at different ratesover time. Thus, the power density to be delivered to a child at age 4will be less than that used for a 5 or 6 year old, for example.

Thus, an operating module of the software can be programmed to retrievefields of data or data files from a patient data entry module that caninclude patient information and other initial observations of parents orclinicians regarding a child’s age, condition, medical history includingmedications that may impact a further diagnostic or therapeutic program.FIG. 16 illustrates a process flow diagram for a method 600 of selectingand optimizing parameters over multiple therapeutic sessions includingmanual and automated selection tracks. Initially, patient data relatedto a child or adult patient (such as age or condition) can be entered bya user into a memory of a computing device (step 602). For example, datacan be entered by a user through the GUI 160 of the remote computingdevice 150 (such as a tablet computing device) and stored in the memory156 as described previously in relation to FIG. 4 . The method 600 canthen follow one of two tracks. In one embodiment, the user can manuallyselect illumination or therapy session parameters for a firsttherapeutic dose level or dose level sequence based upon the patientdata (step 604). For example, the user can manually select parametersfrom menu or other displays on the GUI 160 of the remote computingdevice 150. Then, the illumination and/or therapy session parameters(which may include user-selected parameters and other parameters whetherautomatically determined or set by default) can be displayed on thecomputer display (step 606). For example, the parameters can bedisplayed on the visual display device 152. The device can also beprogrammed to operate a linguistic and/or visual message therapy modulethat communicates auditory and/or visual messages to the patient duringa therapy session.

In an alternative embodiment, the parameters can be set algorithmicallyor automatedly. The processor of the computing device can process thepatient data (including, for example, age and condition data) todetermine the first therapeutic dose level or dose level sequence (step620). For example, the processor 155 of the remote computing device 150can analyze and process the patient data. Then, the automaticallyselected illumination and therapy session parameters (as well as othersession parameters) can be displayed on the display associated with thecomputing device (step 622). Optionally, the set of automaticallyselected parameters can be augmented in this step with additional manualparameters such as an audio or video file used as part of thetherapeutic session.

Whether the parameters are determined automatically or manually, thehead wearable device can then be positioned on the head of patient(e.g., a child or adult) and the therapy session can be actuated basedon the session parameters (step 608). Data related to the patient ordevice during the session can be monitored and recorded. Then, thepatient data (e.g., age or condition data) can be adjusted to optimizesession parameters for future (i.e., second, third, or more) therapeuticsessions (step 610).

FIG. 17 illustrates a process flow diagram for a method 700 foradministering a therapeutic session to a patient in accordance withvarious embodiments described herein. As an optional first step, patientdata can be input by a user to a computing device and stored in datafields in a patient data entry module resident in the computing deviceor a server device (step 702). Relevant patient data entered in thisstep can include patient age, weight, physical or mental condition,medication history or regimen, and a data map of cranial thickness ordensity as a function of location on the patient’s cranium. For example,the patient data entry module can reside in the memory 156 of the remotecomputing device 150, and patient data can be entered using the GUI 160such as by using a keyboard, mouse, or multi-point touch interface 420.This step may be considered optional as the patient data for aparticular patient may already be resident in patient data entry module(e.g., the data may have been entered during previous sessions and neednot be re-entered). The patient data is then retrieved from the datafields in the patient data entry module using the wearable deviceoperating module (step 704). The wearable device operating module candetermine a power level as a function of time for each illumination LED115 a-115 e in the array of the photobiomodulation device 110 based onthe patient data to achieve the minimum therapeutic effect during thetherapeutic session. Once the power levels are determined, thetherapeutic session can be administered to the patient (step 706).

After concluding the therapeutic session, output data can be exported ina format compatible with standard medical records using a medicalrecords module (step 708). Output data can include the illumination timeand/or power for each individual illumination LED, a data distributionof which regions of the brain were illuminated, the cumulative powerdelivered, or annotations from a user conducting the session such as amedical professional. The data can be time-course data including timestamps that record when observations or other data events occurredwithin the therapeutic session.

Shown in FIG. 18 is a further implementation in which the head wearabledevice 800 has light emitting devices 810 at spaced locations around thehead of the patient connected by a cable 812 to a circuit housing havinga first portion with an on/off switch 802 and a second portion with oneor more control buttons or actuators 804 to manually select operatingmodes of the device as described herein. Headphone speakers and/ormicrophones 814 can be mounted to the head worn device 800 orspeakers/microphones can alternatively be within a first tablet 820 thatcan be used by the patient during a therapy session. The first tablet ormobile phone 820 can be connected by wire or cable 806 to device 800 andcan emit sounds or auditory signals for improving linguistic skills ofthe patient as described herein. The display on the first tablet canalso be used to display images or video to the patient during thetherapy session. A second tablet or mobile phone 840 can alsocommunicate with the head worn device 800 and/or the first tablet by acable or wireless connection 808. Tablet 840 can be used by an operatinguser to control operation of one or both of the head worn device 800 andfirst tablet 820, before, during or after a therapy session. Forexample, if an EEG sensor is used during a therapy session, this canserve to monitor the procedure or calibrate the power level to be usedon a particular patient to establish the minimum level therapeutic dose,and optionally to also set a maximum dose for each period ofillumination during the session, and further optionally to select whichregions of the brain of the patient are to be illuminated during asession. The first tablet may be programmed only to provide the auditoryand/or visual components to the patient, whereas the second tablet canbe programmed solely for use by the operator or clinician to manage thetherapy provided to one or more patients in separate sessions.

Throughout the specification and the claims, the following terms take atleast the meanings explicitly associated herein, unless the contextclearly dictates otherwise. The term “or” is intended to mean aninclusive “or.” Further, the terms “a,” “an,” and “the” are intended tomean one or more unless specified otherwise or clear from the context tobe directed to a singular form.

In this description, numerous specific details have been set forth. Itis to be understood, however, that implementations of the disclosedtechnology can be practiced without these specific details. In otherinstances, well-known methods, structures and techniques have not beenshown in detail in order not to obscure an understanding of thisdescription. References to “one embodiment,” “an embodiment,” “someembodiments,” “example embodiment,” “various embodiments,” “oneimplementation,” “an implementation,” “example implementation,” “variousimplementations,” “some implementations,” etc., indicate that theimplementation(s) of the disclosed technology so described can include aparticular feature, structure, or characteristic, but not everyimplementation necessarily includes the particular feature, structure,or characteristic. Further, repeated use of the phrase “in oneimplementation” does not necessarily refer to the same implementation,although it can.

As used herein, unless otherwise specified the use of the ordinaladjectives “first,” “second,” “third,” etc., to describe a commonobject, merely indicate that different instances of like objects arebeing referred to, and are not intended to imply that the objects sodescribed must be in a given sequence, either temporally, spatially, inranking, or in any other manner.

While certain implementations of the disclosed technology have beendescribed in connection with what is presently considered to be the mostpractical and various implementations, it is to be understood that thedisclosed technology is not to be limited to the disclosedimplementations, but on the contrary, is intended to cover variousmodifications and equivalent arrangements included within the scope ofthe appended claims. Although specific terms are employed herein, theyare used in a generic and descriptive sense only and not for purposes oflimitation.

This written description uses examples to disclose certainimplementations of the disclosed technology, including the best mode,and also to enable any person skilled in the art to practice certainimplementations of the disclosed technology, including making and usingany devices or systems and performing any incorporated methods. Thepatentable scope of certain implementations of the disclosed technologyis defined in the claims, and can include other examples that occur tothose skilled in the art. Such other examples are intended to be withinthe scope of the claims if they have structural elements that do notdiffer from the literal language of the claims, or if they includeequivalent structural elements with insubstantial differences from theliteral language of the claims.

Exemplary flowcharts are provided herein for illustrative purposes andare non-limiting examples of methods. One of ordinary skill in the artwill recognize that exemplary methods may include more or fewer stepsthan those illustrated in the exemplary flowcharts, and that the stepsin the exemplary flowcharts may be performed in a different order thanthe order shown in the illustrative flowcharts.

1. A photobiomodulation neuro-therapy device comprising: a portable headmounted device that is sized to be positioned on a patient’s head, theportable head mounted device including a plurality of light emittingdevices, a memory and a battery providing power to the portable headmounted device, each of the light emitting devices being operable inresponse to control signals to control emission of transcranialilluminating light into the patient having a near infrared wavelengthdelivered during a therapeutic period; a processor on the portable headmounted device, the processor being connected to each of the lightemitting devices to execute instructions to communicate the controlsignals that individually control emission of illuminating light fromeach of the light emitting devices during the therapeutic period; and awireless receiver on the portable head mounted device that receiveswireless signals from an external communication device programmed totransmit therapeutic parameters to the portable head mounted device. 2.The device of claim 1 further comprising a transducer device connectedto the processor mounted on a controller board that controls delivery ofan auditory signal to the patient during the therapeutic period.
 3. Thedevice of claim 1 wherein the memory records an amount of thetransmitted light delivered to the patient during the therapeuticperiod.
 4. The device of claim 1 wherein the external communicationdevice comprises a portable display device having a processing device, agraphical user interface and a memory that stores a plurality ofprogrammed modules configured to control one or more operations of theportable head mounted device, the processing device executing a softwareprogram that operates the portable head mounted device.
 5. The device ofclaim 1 wherein the light emitting device further comprises a firstlight emitter that illuminates the patient at a first wavelength and asecond light emitter that illuminates the patient at a second wavelengthdifferent than the first wavelength.
 6. The device of claim 1 whereinthe light emitting device further comprises a plurality of panels thatilluminate the cranium of the patient with the illuminating light from aplurality of different angles, each panel having one or more lightemitting diodes (LEDs) operated at a frequency and duty cycle.
 7. Thedevice of claim 1 further comprising a sensor that measures an operatingcondition of the device or a physiologic response of the patient to theilluminating light and wherein the processor, in response to a sensedvalue from the sensor, controls an operation of the portable headmounted device.
 8. The device of claim 1 wherein the wireless receivercomprises a transceiver such that the transceiver transmits data to theexternal communication device that stores patient data for eachtherapeutic session.
 9. The device of claim 8 wherein the externalcommunication device comprises a user interface that controls anoperation of the portable head mounted device.
 10. The device of claim 1wherein the portable head mounted device has a size, shape and weight tobe worn by a child, and wherein the processor is programmed to treat aneurological condition that comprises autism.
 11. The device of claim 1further comprising a graphical user interface is operable on thetouchscreen display that is responsive to a plurality of touch gestureswhereby a user can control one or more operating parameters of theportable head mounted device.
 12. The device of claim 6 wherein eachpanel in the plurality of panels comprises an LED circuit board on whichthe at least one light emitting diode is mounted, each LED circuit boardbeing connected to a power control circuit mounted on a rear portion ofthe portable head mounted device, at least one LED being positioned onthe portable head mounted device to transmit light through the craniuminto a frontal lobe, at least a second LED being positioned on theportable head mounted device to transmit light through the cranium intoa temporal lobe, and at least a third LED on the portable head mounteddevice to transmit light through the cranium and into the occipitallobe.
 13. The device of claim 12 wherein the battery is connected to thepower control circuit mounted on a controller circuit board, the batterybeing attached to a battery holder on the portable head mounted devicesuch that the battery in the battery holder can be replaced.
 14. Thedevice of claims 1 wherein the external communication device can beselectively connected to the head wearable device with a cable.
 15. Thedevice of claim 1 wherein the external communication device comprises atablet display device having a touchscreen display that is operative inresponse to a plurality of touch gestures made by a user on the surfaceof the touchscreen display, the tablet display device including aprocessor programmed with one or more software modules to controloperations of the tablet display device and the portable head mounteddevice.
 16. The device of claim 7 wherein the processor, in response tosensed data, operates to control power distribution to each of the lightemitting devices.
 17. The device of claim 1 wherein each light emittingdevice can be adjusted to different positions on the portable headmounted device and the total power emitted by each light emitting devicecan be incremented between different power levels.
 18. The device ofclaim 1 wherein the light emitting devices operate in response toprogrammed instructions such that the processor executes a sequence ofsteps to illuminate different regions of brain tissue of the patientwith selected levels of light.
 19. The device of claim 18 wherein theselected levels of light comprise a plurality of presets such that auser can select at least one preset that includes a time duration, atotal area of a cranium of the patient to be automatically illuminatedand a total amount of light to be delivered through the total area ofthe cranium of the patient during the therapeutic session.
 20. Thedevice of claim 18 wherein the selected levels of light are manuallyselected by a user with a user interface on the external communicationdevice.